ml5.js vs Tensorflow Lite | What are the differences? | StackShare

Tensorflow Lite vs ml5.js

Overview

ml5.js

Stacks5

Followers53

Votes0

GitHub Stars6.6K

Forks908

Tensorflow Lite

Stacks74

Followers144

Votes1

ml5.js vs Tensorflow Lite: What are the differences?

Developers describe ml5.js as "Friendly machine learning for the web". ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies. On the other hand, Tensorflow Lite is detailed as "Deploy machine learning models on mobile and IoT devices". It is a set of tools to help developers run TensorFlow models on mobile, embedded, and IoT devices. It enables on-device machine learning inference with low latency and a small binary size.

ml5.js and Tensorflow Lite can be primarily classified as "Machine Learning" tools.

ml5.js is an open source tool with 3.65K GitHub stars and 339 GitHub forks. Here's a link to ml5.js's open source repository on GitHub.

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Detailed Comparison

ml5.js	Tensorflow Lite
ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.	It is a set of tools to help developers run TensorFlow models on mobile, embedded, and IoT devices. It enables on-device machine learning inference with low latency and a small binary size.
Pre-trained models for detecting human poses, generating text, styling an image with another, composing music, pitch detection, and common English language word relationships; API for training new models based on pre-trained ones as well as training from custom user data from scratch	Lightweight solution for mobile and embedded devices; Enables low-latency inference of on-device machine learning models with a small binary size; Fast performance
Statistics
GitHub Stars 6.6K	GitHub Stars -
GitHub Forks 908	GitHub Forks -
Stacks 5	Stacks 74
Followers 53	Followers 144
Votes 0	Votes 1
Pros & Cons
No community feedback yet	Pros 1 .tflite conversion
Integrations
No integrations available	Python Android OS iOS Raspberry Pi

What are some alternatives to ml5.js, Tensorflow Lite?

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

Kubeflow

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

TensorFlow.js

Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API

Polyaxon

An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.

Streamlit

It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

MLflow

MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

H2O

H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.